diff --git a/README.md b/README.md
index f391c937..be68f685 100644
--- a/README.md
+++ b/README.md
@@ -203,7 +203,117 @@ response = agent.run("Generate a video of a swarm of fish and then make an image
 print(response)
 ```
 
+---
+
+### Multi-Agent Swarm for Logistics
+- Swarms is a framework designed for real-world deployment here is a demo presenting a fully ready to use Swarm for a vast array of logistics tasks.
+- Swarms is designed to be modular and reliable for real-world deployments.
+- Swarms is the first framework that unleases multi-modal autonomous agents in the real world.
+
+```python
+from swarms.structs import Agent
+import os
+from dotenv import load_dotenv
+from swarms.models import GPT4VisionAPI
+from swarms.prompts.logistics import (
+    Health_Security_Agent_Prompt,
+    Quality_Control_Agent_Prompt,
+    Productivity_Agent_Prompt,
+    Safety_Agent_Prompt,
+    Security_Agent_Prompt,
+    Sustainability_Agent_Prompt,
+    Efficiency_Agent_Prompt,
+)
+
+# Load ENV
+load_dotenv()
+api_key = os.getenv("OPENAI_API_KEY")
 
+# GPT4VisionAPI 
+llm = GPT4VisionAPI(openai_api_key=api_key)
+
+# Image for analysis
+factory_image = "factory_image1.jpg"
+
+# Initialize agents with respective prompts
+health_security_agent = Agent(
+    llm=llm,
+    sop=Health_Security_Agent_Prompt,
+    max_loops=1,
+    multi_modal=True,
+)
+
+# Quality control agent
+quality_control_agent = Agent(
+    llm=llm,
+    sop=Quality_Control_Agent_Prompt,
+    max_loops=1,
+    multi_modal=True,
+)
+
+
+# Productivity Agent
+productivity_agent = Agent(
+    llm=llm,
+    sop=Productivity_Agent_Prompt,
+    max_loops=1,
+    multi_modal=True,
+)
+
+# Initiailize safety agent
+safety_agent = Agent(
+    llm=llm, sop=Safety_Agent_Prompt, max_loops=1, multi_modal=True
+)
+
+# Init the security agent
+security_agent = Agent(
+    llm=llm, sop=Security_Agent_Prompt, max_loops=1, multi_modal=True
+)
+
+
+# Initialize sustainability agent
+sustainability_agent = Agent(
+    llm=llm,
+    sop=Sustainability_Agent_Prompt,
+    max_loops=1,
+    multi_modal=True,
+)
+
+
+# Initialize efficincy agent
+efficiency_agent = Agent(
+    llm=llm,
+    sop=Efficiency_Agent_Prompt,
+    max_loops=1,
+    multi_modal=True,
+)
+
+# Run agents with respective tasks on the same image
+health_analysis = health_security_agent.run(
+    "Analyze the safety of this factory", factory_image
+)
+quality_analysis = quality_control_agent.run(
+    "Examine product quality in the factory", factory_image
+)
+productivity_analysis = productivity_agent.run(
+    "Evaluate factory productivity", factory_image
+)
+safety_analysis = safety_agent.run(
+    "Inspect the factory's adherence to safety standards",
+    factory_image,
+)
+security_analysis = security_agent.run(
+    "Assess the factory's security measures and systems",
+    factory_image,
+)
+sustainability_analysis = sustainability_agent.run(
+    "Examine the factory's sustainability practices", factory_image
+)
+efficiency_analysis = efficiency_agent.run(
+    "Analyze the efficiency of the factory's manufacturing process",
+    factory_image,
+)
+```
 ---
 
 # Features 🤖 
diff --git a/playground/demos/multi_modal_chain_of_thought/vcot.py b/playground/demos/multi_modal_chain_of_thought/vcot.py
new file mode 100644
index 00000000..e69de29b
diff --git a/pyproject.toml b/pyproject.toml
index 4e1c1c7c..c9f620a0 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -4,7 +4,7 @@ build-backend = "poetry.core.masonry.api"
 
 [tool.poetry]
 name = "swarms"
-version = "2.7.7"
+version = "2.7.8"
 description = "Swarms - Pytorch"
 license = "MIT"
 authors = ["Kye Gomez <kye@apac.ai>"]